Displaying Fear, Sadness, and Joy in Public: Schizophrenia Vloggers' Video Narration of Emotion and Online Care-Seeking

2025-02-28

AI Summary

This study investigates how individuals with schizophrenia express fear, sadness, and joy in YouTube vlogs through multimodal strategies—linguistic (e.g., affective narratives) and visual (e.g., camera orientation, anonymity, immediacy)—and how these expressions shape their online help-seeking behaviors. Drawing on a corpus of 401 patient-generated vlogs, we employed content analysis and multimodal discourse analysis, integrating qualitative coding with quantitative interaction metrics (views, likes, comments) for triangulation. Our analysis systematically identifies three affective expression patterns and three visual framing strategies. Crucially, we uncover a “visual appeal disparity”: higher visual production quality significantly and positively predicts public engagement, underscoring the critical role of platform interface design in mediating equitable support access for vulnerable populations. These findings provide empirical grounding and actionable insights for designing inclusive video platforms tailored to individuals with severe mental illness.

Technology Category

• Computer Vision: Multi-modal Vision
• Machine Learning: Multimodal Learning
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Economics, Online Markets and Human Computation: The sharing economy
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

Individuals with severe mental illnesses (SMI), particularly schizophrenia, experience complex and intense emotions frequently. They increasingly turn to vlogging as an authentic medium for emotional disclosure and online support-seeking. While previous research has primarily focused on text-based disclosure, little is known about how people construct narratives around emotions and emotional experiences through video blogs. Our study analyzed 401 YouTube videos created by schizophrenia vloggers, revealing that vloggers disclosed their fear, sadness, and joy through verbal narration by explicit expressions or storytelling. Visually, they employed various framing styles, including Anonymous, Talk-to-Camera, and In-the-Moment approaches, along with diverse visual narration techniques. Notably, we uncovered a concerning 'visual appeal disparity' in audience engagement, with visually appealing videos receiving significantly more views, likes, and comments. This study discusses the role of video-sharing platforms in emotional expression and offers design implications for fostering online care-seeking for emotionally vulnerable populations.

Problem

• Explores emotional expression in schizophrenia vloggers' videos.
• Investigates visual and verbal narration techniques in vlogs.
• Examines audience engagement disparities in emotional support-seeking.

Innovation

• Analyzed 401 schizophrenia vloggers' YouTube videos
• Identified verbal and visual emotion narration techniques
• Discovered visual appeal disparity in audience engagement